Adaptive Personalized Federated Learning (APFL) [1]} learns a personalized model for each user that is a mixture of the local and global models. The optimal mixing parameter, which controls the local and global models' ratio, is integrated into the learning problem. Another approach FedPer [2]} divides a deep neural network into the base and personalization layers to learn the base layers collaboratively and personalization layers specific to each user.
